JAK inhibitors and the risk of malignancy: a meta-analysis across disease indications.

OBJECTIVES: To estimate the association of Janus kinase inhibitors (JAKi) with the incidence of malignancy, compared with placebo, tumour necrosis factor (TNF)-α inhibitors (TNFi) and methotrexate. METHODS: Systematic searches of databases were performed, to December 2022, to identify phase II/III/IV randomised clinical trials (RCTs) and long-term extension (LTE) studies of JAKi (tofacitinib, baricitinib, upadacitinib, filgotinib, peficitinib) compared with placebo, TNFi or methotrexate, in adults with rheumatoid arthritis, psoriatic arthritis, psoriasis, axial spondyloarthritis, inflammatory bowel disease or atopic dermatitis. Network and pairwise meta-analyses were performed to estimate incidence rate ratios (IRRs) for malignancy between JAKi and comparators. Bias was assessed using the Cochrane Risk of Bias-2 tool. RESULTS: In 62 eligible RCTs and 16 LTE studies, there were 82 366 person-years of exposure to JAKi, 2924 to placebo, 7909 to TNFi and 1074 to methotrexate. The overall malignancy incidence rate was 1.15 per 100 person-years in RCTs, and 1.26 per 100 person-years across combined RCT and LTE data. In network meta-analyses, the incidence of all malignancies including non-melanomatous skin cancers (NMSCs) was not significantly different between JAKi and placebo (IRR 0.71; 95% CI 0.44 to 1.15) or between JAKi and methotrexate (IRR 0.77; 95% CI 0.35 to 1.68). Compared with TNFi, however, JAKi were associated with an increased incidence of malignancy (IRR 1.50; 95% CI 1.16 to 1.94). Findings were consistent when analysing NMSC only and when analysing combined RCT/LTE data. CONCLUSIONS: JAKi were associated with a higher incidence of malignancy compared with TNFi but not placebo or methotrexate. Cancers were rare events in all comparisons. PROSPERO REGISTRATION NUMBER: CRD42022362630.

Implementing treat-to-target urate-lowering therapy during hospitalisations for gout flares.

OBJECTIVES: To evaluate a strategy designed to optimise care and increase uptake of urate-lowering therapy (ULT) during hospitalisations for gout flares. METHODS: We conducted a prospective cohort study to evaluate a strategy that combined optimal in-hospital gout management with a nurse-led, follow-up appointment, followed by handover to primary care. Outcomes, including ULT initiation, urate target attainment, and re-hospitalisation rates, were compared between patients hospitalised for flares in the 12 months post-implementation and a retrospective cohort of hospitalised patients from 12 months pre-implementation. RESULTS: 119 and 108 patients, respectively, were hospitalised for gout flares in the 12 months pre- and post-implementation. For patients with 6-month follow-up data available (n = 94 and n = 97, respectively), the proportion newly initiated on ULT increased from 49.2% pre-implementation to 92.3% post-implementation (age/sex-adjusted odds ratio (aOR) 11.5; 95% confidence interval (CI) 4.36-30.5; p < 0.001). After implementation, more patients achieved a serum urate ≤360 micromol/L within 6 months of discharge (10.6% pre-implementation vs. 26.8% post-implementation; aOR 3.04; 95% CI 1.36-6.78; p = 0.007). The proportion of patients re-hospitalised for flares was 14.9% pre-implementation vs. 9.3% post-implementation (aOR 0.53, 95% CI 0.22 to 1.32; p = 0.18). CONCLUSION: Over 90% of patients were initiated on ULT after implementing a strategy to optimise hospital gout care. Despite increased initiation of ULT during flares, recurrent hospitalisations were not more frequent following implementation. Significant relative improvements in urate target attainment were observed post-implementation; however, for the majority of hospitalised gout patients to achieve urate targets, closer primary-secondary care integration is still needed.

A Systematic Review and Metaanalysis of Predictors of Mortality in Idiopathic Inflammatory Myopathy-Associated Interstitial Lung Disease.

OBJECTIVE: Idiopathic inflammatory myopathy (IIM)-associated interstitial lung disease (ILD) can range from rapidly progressive disease with high mortality to indolent disease with minimal morbidity. This systematic review and metaanalysis describe immunological, clinical, and radiographical predictors of mortality in IIM-ILD. METHODS: MEDLINE and Embase database searches were completed on October 18, 2021, to identify articles providing survival data according to baseline characteristics in patients with concurrent IIM and ILD. Prognostic factors common to more than 5 papers were included in the metaanalysis using a random-effects model to report odds ratios (ORs) for binary variables and Hedges g for continuous variables. Risk of bias was assessed using the Newcastle-Ottawa Scale score and the Egger test for publication bias. RESULTS: From 4433 articles, 62 papers were suitable for inclusion; among these studies, 38 different variables were considered. The OR for risk of death regarding the presence of anti-melanoma differentiation-associated protein 5 (MDA5) antibodies was 6.20 (95% CI 3.58-10.71), and anti-tRNA synthetase antibodies were found to be protective (OR 0.24, 95% CI 0.14-0.41). Neither antinuclear antibodies, anti-52-kDa Ro antigen antibodies, nor SSA significantly altered mortality, nor was MDA5 titer predictive. Examples of prognostic factors that are significantly associated with mortality in this study include the following: age; male sex; acute/subacute onset; clinically amyopathic dermatomyositis; dyspnea; ulceration; fever; raised C-reactive protein, ferritin, lactate dehydrogenase, alveolar to arterial O2 (A-aO2) gradient, ground-glass opacity on high-resolution computed tomography (HRCT), and overall HRCT score; and reduced albumin, lymphocytes, ratio of partial pressure of oxygen in the arterial blood to fraction of inspired oxygen (PF ratio), percentage predicted transfer factor for carbon monoxide, and percentage predicted forced vital capacity. Baseline surfactant protein-D and Krebs von den Lungen-6 levels were not predictors of mortality. CONCLUSION: Many mortality risk factors were identified, though heterogeneity was high, with a low quality of evidence and a risk of publication bias. Studies regarding anti-MDA5 antibody-positive disease and and those from East Asia predominate, which could mask risk factors relevant to other IIM subgroups or populations.

Hospital Mortality and Resource Implications of Hospitalisation with COVID-19 in London, UK: A Prospective Cohort Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) had a significant impact on the National Health Service in the United Kingdom (UK), with over 35 000 cases reported in London by July 30, 2020. Detailed hospital-level information on patient characteristics, outcomes, and capacity strain is currently scarce but would guide clinical decision-making and inform prioritisation and planning. METHODS: We aimed to determine factors associated with hospital mortality and describe hospital and ICU strain by conducting a prospective cohort study at a tertiary academic centre in London, UK. We included adult patients admitted to the hospital with laboratory-confirmed COVID-19 and followed them up until hospital discharge or 30 days. Baseline factors that are associated with hospital mortality were identified via semiparametric and parametric survival analyses. RESULTS: Our study included 429 patients: 18% of them were admitted to the ICU, 52% met criteria for ICU outreach team activation, and 61% had treatment limitations placed during their admission. Hospital mortality was 26% and ICU mortality was 34%. Hospital mortality was independently associated with increasing age, male sex, history of chronic kidney disease, increasing baseline C-reactive protein level, and dyspnoea at presentation. COVID-19 resulted in substantial ICU and hospital strain, with up to 9 daily ICU admissions and 41 daily hospital admissions, to a peak census of 80 infected patients admitted in the ICU and 250 in the hospital. Management of such a surge required extensive reorganisation of critical care services with expansion of ICU capacity from 69 to 129 beds, redeployment of staff from other hospital areas, and coordinated hospital-level effort. CONCLUSIONS: COVID-19 is associated with a high burden of mortality for patients treated on the ward and the ICU and required substantial reconfiguration of critical care services. This has significant implications for planning and resource utilisation.